Large language model

Conversational AI describes systems that understand and respond in natural language across chat, email, and voice. The category spans intent-based bots and modern language-model agents, and the practical difference between them is whether the system can only reply or can also take action in business systems.

Grounding is the practice of constraining an AI agent’s answers to approved knowledge sources and live system data rather than to the model’s own training. Grounding is the main defence against hallucination, and it is what makes an AI answer auditable back to a specific document or record.

Retrieval-augmented generation grounds answers by retrieving an organisation’s own documents at the moment of answering and passing them to the model as context. It keeps responses current without retraining, and it makes each answer traceable to the specific source the system actually consulted.

A prompt is the instruction set that defines how an AI agent behaves in a given task, covering role, tone, permitted actions, and output format. Prompts express intent but do not enforce it, which is why hard limits belong in guardrails rather than in prompt wording.